code: def _generate_rand_meta(
      obj, dtypes_list, null_frequency_override=None
  ):
      obj._current_params = {}
      num_rows = obj._rand(obj._max_rows)
      num_cols = obj._rand(obj._max_columns)
  
      dtypes_meta = []
  
      for _ in range(num_cols):
          dtype = random.choice(dtypes_list)
          null_frequency = (
              random.uniform(0, 1)
              if null_frequency_override is None
              else null_frequency_override
          )
          # `cardinality` has to be at least 1.
          cardinality = max(1, obj._rand(obj._max_rows))
          meta = dict()
          if dtype == "str":
              # We want to operate near the limits of string column
              # Hence creating a string column of size almost
              # equal to 2 Billion bytes(sizeof(int))
              if obj._max_string_length is None:
                  meta["max_string_length"] = random.randrange(
                      0, int(2000000000 / num_rows)
                  )
              else:
                  meta["max_string_length"] = obj._max_string_length
          elif dtype == "list":
              if obj._max_lists_length is None:
                  meta["lists_max_length"] = np.random.randint(
                      0, 2000000000
                  )
              else:
                  meta["lists_max_length"] = obj._max_lists_length
  
              if obj._max_lists_nesting_depth is None:
                  meta["nesting_max_depth"] = np.random.randint(
                      1, np.iinfo("int64").max
                  )
              else:
                  meta[
                      "nesting_max_depth"
                  ] = obj._max_lists_nesting_depth
  
              meta["value_type"] = random.choice(
                  list(cudf.utils.dtypes.ALL_TYPES - {"category"})
              )
          elif dtype == "struct":
              if obj._max_lists_nesting_depth is None:
                  meta["nesting_max_depth"] = np.random.randint(2, 10)
              else:
                  meta[
                      "nesting_max_depth"
                  ] = obj._max_lists_nesting_depth
  
              if obj._max_struct_null_frequency is None:
                  meta["max_null_frequency"] = random.uniform(0, 1)
              else:
                  meta[
                      "max_null_frequency"
                  ] = obj._max_struct_null_frequency
  
              if obj._max_struct_types_at_each_level is None:
                  meta["max_types_at_each_level"] = np.random.randint(
                      low=1, high=10
                  )
              else:
                  meta[
                      "max_types_at_each_level"
                  ] = obj._max_struct_types_at_each_level
  
          elif dtype == "decimal64":
              meta["max_precision"] = cudf.Decimal64Dtype.MAX_PRECISION
          elif dtype == "decimal32":
              meta["max_precision"] = cudf.Decimal32Dtype.MAX_PRECISION
  
          meta["dtype"] = dtype
          meta["null_frequency"] = null_frequency
          meta["cardinality"] = cardinality
          dtypes_meta.append(meta)
      return dtypes_meta, num_rows, num_cols
  
file_path: cudf/python/cudf/cudf/_fuzz_testing/utils.py
imports: import random
  import fastavro
  import numpy
  import pandas
  import pyarrow
  import cudf
  from cudf.testing._utils import assert_eq
  from cudf.utils.dtypes import pandas_dtypes_to_np_dtypes, pyarrow_dtypes_to_pandas_dtypes
label_desc: Use image node_id 1 for calling a global function with example usage: _generate_rand_meta(obj, dtypes_list, null_frequency_override) and returns: dtypes_meta,  num_rows,  num_cols